First of Its Kind Software Uses AI and ML for Personalized Disease Prediction

Currently, no artificial intelligence (AI) or machine-learning tools are available for investigating and interpreting the complete human genome, particularly for non-experts. Now, a first-of-its-kind software combines AI and machine-learning approaches to understand the importance of specific genomic biomarkers to predict diseases in individuals.

The IntelliGenes software created by researchers at Rutgers Health (New Brunswick, NJ, USA) combines conventional statistical methods with cutting-edge machine learning algorithms to generate personalized patient predictions and provide a visual representation of the biomarkers significant to disease prediction. IntelliGenes has been designed in such as way that the platform can be used by anyone, including students or those lacking strong knowledge of bioinformatics techniques or access to high-performing computers.

In a study, the researchers demonstrated how IntelliGenes can be deployed by a wide range of users to analyze multigenomic and clinical data. In another study, the researchers applied IntelliGenes to discover novel biomarkers and predict cardiovascular disease with high accuracy. Researchers also tested the software using Amarel, the high-performance computing cluster managed by the Rutgers Office of Advanced Research Computing.

“IntelliGenes can support personalized early detection of common and rare diseases in individuals, as well as open avenues for broader research ultimately leading to new interventions and treatments,” said Zeeshan Ahmed, lead author of the study and a faculty member at Rutgers Institute for Health, Health Care Policy and Aging Research (IFH).

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